LFM2.5-2.6B

Liquid AI's on-device agentic model, released Aug 6 2026 (surfaced on hosted platforms ~Aug 11) — a 2.69B-parameter dense model, distinct from the LFM2.5-8B-A1B MoE. Uses Liquid's hybrid stack across 30 layers: 22 double-gated short-convolution blocks plus 8 grouped-query-attention blocks, with a 128K-token vocabulary and a 131,072-token context, pre-trained on ~34T tokens across 16 languages. Text-only, built to plan, call tools, and complete multi-step tasks entirely on-device (phone, laptop, PC, or robot) so data never leaves the device and the marginal cost per run is near zero; Liquid reports tool-use and instruction-following competitive with models ~4x its size (e.g. leading Qwen3.5-9B on ToolSandbox, Multi-IF, and IFStruct), while explicitly not recommending it for agentic coding or knowledge-heavy work. Decodes at ~220 tok/s on an Apple M5 Max in under 2.5GB and ~30 tok/s on a phone. Open weights (base + post-trained) on Hugging Face under the LFM Open License (lfm1.0), shipped day-one in GGUF, MLX, and ONNX.